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The MSc Linguistics and Artificial Intelligence blends linguistic theory with AI and NLP, preparing students to analyse language data using computational methods. It suits students from humanities or technical backgrounds who want to work at the intersection of language, data, and machine learning.
Curriculum structure
Students begin with Foundations of Computational Linguistics and Programming for the Humanities, learning core linguistic concepts and basic coding. They progress to modules like Analysing Language Datasets and AI & Analytical Modelling, applying machine learning to large text datasets. The programme ends with a Dissertation combining linguistic insight and AI methods.
Focus areas: “computational linguistics, NLP, machine learning for language data”
Learning outcomes: “analyse language data, build/evaluate NLP models, conduct independent research”
Professional alignment: Prepares graduates for roles in NLP, language technology, and data analysis.
Reputation: Strong research profile and good employability in AI-language industries.
Students gain practical skills by applying computational linguistics and AI techniques to language data, using QMUL's specialist computing facilities and language resources. This applied learning is central to the curriculum:
Software: Training in Python with key NLP libraries (NLTK, spaCy, Transformers).
Language Data: Hands-on work with linguistic corpora and speech datasets.
Research Project: An individual dissertation in computational linguistics or NLP.
Facilities: Access to QMUL's computing labs and language research resources.
Research Context: Links to the Language, Cognition and Computation research group.
Graduates of Queen Mary University of London's MSc Linguistics and AI gain expertise in computational linguistics, Python programming, machine learning for language data, and statistical analysis, enabling innovative applications in natural language processing and AI-driven language technologies. The program equips alumni with skills to analyze large datasets and develop AI models for sectors like tech, marketing, and social media, fostering critical research and industry readiness. Typical job roles: computational linguist, NLP engineer, AI researcher, language data scientist.
University services: Careers service offers CV workshops, mock interviews, job fairs, alumni networking, and linguistics-specific training.
Employment stats/salary: 93% employed or in study within 15 months; roles start at £35,000–£50,000.
Partnerships: Collaborations with tech firms for AI language projects and datasets.
Accreditation value: QMUL's linguistics department prestige ensures enduring industry recognition.
Outcomes: Careers in NLP, tech, marketing, research; high PhD progression.
Further Academic Progression: Pursue PhD in computational linguistics, AI, or NLP at QMUL, extending dissertation on language models.
A 2:1 or above at undergraduate level in any subjectUSA- UK 2:1 degree: GPA 3.2 out of 4.0India - Bachelor Degree (minimum 3 years) from selected institutions. UK 2:1 degree: 60% to 70% IELTS (Academic) minimum score 7.0 overall with 6.0 in each of Writing, Listening, Reading and Speaking TOEFL minimum score 100 overall with 21 in Writing, 19 in Reading, 18 in Listening and 21 in SpeakingComputational LinguistNLP EngineerAI Language SpecialistConversational AI DesignerSpeech Technology DeveloperLanguage Data ScientistAI Localization SpecialistSearch Engine AnalystLinguistic Technology ConsultantVoice User Interface DesignerAI Content StrategistDigital Humanities Researcher
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Queen Mary University of London
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